Citations

AbstractIn a COVID‐19 sero‐surveillance cohort study with predominantly healthy and vaccinated individuals, the objectives were (i) to investigate longitudinally the factors associated with the quantitative dynamics of antispike (anti‐S1) IgG antibody levels, (ii) to evaluate whether the levels were associated with protection from SARS‐CoV‐2 infection, and (iii) to assess whether the association was different in the pre‐Omicron compared with the Omicron period. The QuantiVac Euroimmun ELISA test was used to quantify anti‐S1 IgG levels. The entire study period (16 months), the 11‐month pre‐Omicron period and the cross‐sectional analysis before the Omicron surge included 3219, 2310, and 895 reactive serum samples from 949, 919, and 895 individuals, respectively. Mixed‐effect linear, mixed‐effect time‐to‐event, and logistic regression models were used to achieve the objectives. Age and time since infection or vaccination were the only factors associated with a decline of anti‐S1 IgG levels. Higher antibody levels were significantly associated with protection from SARS‐CoV‐2 infection (0.89, 95% confidence interval [CI] 0.82–0.97), and the association was higher during the time period when Omicron was predominantly circulating compared with the ones when Alpha and Delta variants were predominant (adjusted hazard ratio for interaction 0.66, 95% CI 0.53–0.84). In a prediction model, it was estimated that >8000 BAU/mL anti‐S1 IgG was required to reduce the risk of infection with Omicron variants by approximately 20%–30% for 90 days. Though, such high levels were only found in 1.9% of the samples before the Omicron surge, and they were not durable for 3 months. Anti‐S1 IgG antibody levels are statistically associated with protection from SARS‐CoV‐2 infection. However, the prediction impact of the antibody level findings on infection protection is limited.

Aims Reticulin stain is used routinely in the histological evaluation of hepatocellular carcinoma (HCC). The goal of this study was to assess whether the histological reticulin proportionate area (RPA) in HCCs predicts tumour‐related outcomes. Methods and results We developed and validated a supervised artificial intelligence (AI) model that utilises a cloud‐based, deep‐learning AI platform (Aiforia Technologies, Helsinki, Finland) to specifically recognise and quantify the reticulin framework in normal livers and HCCs using routine reticulin staining. We applied this reticulin AI model to a cohort of consecutive HCC cases from patients undergoing curative resection between 2005 and 2015. A total of 101 HCC resections were included (median age = 68 years, 64 males, median follow‐up time = 49.9 months). AI model RPA reduction of > 50% (compared to normal liver tissue) was predictive of metastasis [hazard ratio (HR) = 3.76, P = 0.004, disease‐free survival (DFS, HR = 2.48, P < 0.001) and overall survival (OS), HR = 2.80, P = 0.001]. In a Cox regression model, which included clinical and pathological variables, RPA decrease was an independent predictor of DFS and OS and the only independent predictor of metastasis. Similar results were found in the moderately differentiated HCC subgroup (WHO grade 2), in which reticulin quantitative analysis was an independent predictor of metastasis, DFS and OS. Conclusion Our data indicate that decreased RPA is a strong predictor of various HCC‐related outcomes, including within the moderately differentiated subgroup. Reticulin, therefore, may represent a novel and important prognostic HCC marker, to be further explored and validated.

Objectives: An unexpectedly low word recognition (WR) score may be taken as evidence of increased risk for retrocochlear tumor. We sought to develop evidence for or against using a standardized WR (sWR) score in detecting retrocochlear tumors. The sWR is a z score expressing the difference between an observed WR score and a Speech Intelligibility Index–based predicted WR score. We retrospectively compared the sensitivity and specificity of pure-tone asymmetry-based logistic regression models that incorporated either the sWR or the raw WR scores in detecting tumor cases. Two pure-tone asymmetry calculations were used: the 4-frequency pure-tone asymmetry (AAO) calculation of the American Academy of Otolaryngology–Head and Neck Surgery and a 6-frequency pure-tone asymmetry (6-FPTA) calculation previously optimized to detect retrocochlear tumors. We hypothesized that a regression model incorporating the 6-FPTA calculation and the sWR would more accurately detect retrocochlear tumors. Design: Retrospective data from all patients seen in the audiology clinic at Mayo Clinic in Florida in 2016 were reviewed. Cases with retrocochlear tumors were compared with a reference group with noise- or age-related hearing loss or idiopathic sensorineural hearing loss. Two pure-tone–based logistic regression models were created (6-FPTA and AAO). Into these base models, WR variables (WR, sWR, WR asymmetry [WRΔ], and sWR asymmetry [sWRΔ]) were added. Tumor detection performance for each regression model was compared twice: first, using all qualifying cases (61 tumor cases; 2332 reference group cases), and second, using a data set filtered to exclude hearing asymmetries greater than would be expected from noise-related or age-related hearing loss (25 tumor cases; 2208 reference group cases). The area under the curve and the DeLong test for significant receiver operating curve differences were used as outcome measures. Results: The 6-FPTA model significantly outperformed the AAO model—with or without the addition of WR or WRΔ variables. Including sWR into the AAO base regression model significantly improved disease detection performance. Including sWR into the 6-FPTA model significantly improved disease detection performance when large hearing asymmetries were excluded. In the data set that included large pure-tone asymmetries, area under the curve values for the 6-FPTA + sWR and AAO + sWR models were not significantly better than the base 6-FPTA model. Conclusions: The results favor the superiority of the sWR computational method in identifying reduced WR scores in retrocochlear cases. The utility would be greatest where undetected tumor cases are embedded in a population heavily representing age- or noise-related hearing loss. The results also demonstrate the superiority of the 6-FPTA model in identifying tumor cases. The 2 computational methods may be combined (ie, the 6-FPTA + sWR model) into an automated tool for detecting retrocochlear disease in audiology and community otolaryngology clinics. The 4-frequency AAO-based regression model was the weakest detection method considered. Including raw WR scores into the model did not improve performance, whereas including sWR into the model did improve tumor detection performance. This further supports the contribution of the sWR computational method for recognizing low WR scores in retrocochlear disease cases.

Anaplasma phagocytophilum is an obligate intracellular, Gram-negative pathogen, causative agent of Human Granulocytic Anaplasmosis (HGA). HGA usually manifests as a non-specific febrile illness, accompanied by evidence of leucopenia, thrombocytopenia, and an alteration in liver enzymes. Neurologic manifestations of anaplasmosis are rare and rarely reported. We describe a 62-year-old man who developed encephalitis due to an Anaplasma phagocytophilum infection. The patient favorably responded to intravenous doxycycline and recovered without neurological sequela. In the tick endemic area, clinicians should have a high index of suspicion for tick-borne diseases in patients presenting with neurological deficits. A prompt diagnosis and treatment lead to improvements in morbidity and mortality.

Merkel cell carcinoma (MCC) has a tendency for lymphatic spread and locoregional recurrence, although there is little data examining the risk factors for patients with lymph node-positive extremity lesions. The purpose of the current study was to examine the outcomes and risk factors associated with nodal metastasis in extremity MCC. We retrospectively reviewed the medical record of 120 patients with extremity MCC evaluated at our institution between 1994 and 2021. The mean age of this cohort was 71 years; 33% of patients were female; and 98% were Caucasian. Seventy-eight (65%) patients presented with localized disease. Thirty-seven (31%) patients had stage III disease, and five (4%) patients had stage IV disease. Treatment of primary lesions consisted primarily of margin-negative excision and adjuvant radiotherapy. Nodal metastases were most treated with adjuvant radiation or completion lymph node dissection. Five-year disease-specific survival in our series was 88% for patients with localized disease, 89% for stage IIIa disease, 40% for stage IIIb disease and 42% for stage IV. Factors associated with worse survival included immunosuppression and macroscopic nodal disease. In conclusion, extremity MCC has a low rate of local recurrence when treated with margin-negative excision and adjuvant radiation. However, treatment of nodal metastases remains a challenge with high rates of recurrence and mortality, particularly for patients who are immunosuppressed or who have macroscopic nodal disease.

Transcatheter valve replacement (TAVR) is a rapidly developing modality to treat patients with aortic stenosis (AS). Conduction disease post TAVR is one of the most frequent and serious complications experienced by patients. Multiple factors contribute to the risk of conduction disease, including AS and the severity of valve calcification, patients’ pre-existing conditions (i.e., conduction disease, anatomical variations, and short septum) in addition to procedure-related factors (e.g., self-expanding valves, implantation depth, valve-to-annulus ratio, and procedure technique). Detailed evaluation of risk profiles could allow us to better prevent, recognize, and treat this entity. Available evidence on management of conduction disease post TAVR is based on expert opinion and varies widely. Currently, conduction disease in TAVR patients is managed depending on patient risk, with minimal-to-no inpatient/outpatient observation, inpatient monitoring (24–48 h) followed by ambulatory monitoring, or either prolonged inpatient and outpatient monitoring or permanent pacemaker implantation. Herein, we review the incidence and risk factors of TAVR-associated conduction disease and discuss its management.

Melanoma is the leading cause of death from cutaneous malignancy. While targeted therapy and immunotherapy with checkpoint inhibitors have significantly decreased the mortality rate of this disease, advanced melanoma remains a therapeutic challenge. Here, we confirmed that interferon-gamma (IFN-γ)-induced PD-L1 expression in melanoma cell lines. This increased expression was down-regulated by the reduction in phosphorylated STAT3 signaling via MET tyrosine kinase inhibitor treatment. Furthermore, immunoprecipitation and confocal immunofluorescence microscopy analysis reveals MET and PD-L1 protein–protein interaction and colocalization on the cell surface membrane of melanoma cells. Together, these findings demonstrate that the IFN-γ-induced PD-L1 expression in melanoma cells is negatively regulated by MET inhibition through the JAK/STAT3 signaling pathway and establish the colocalization and interaction between an RTK and a checkpoint protein in melanoma cells.

Objective Noise quantification is fundamental to computed tomography (CT) image quality assessment and protocol optimization. This study proposes a deep learning–based framework, Single-scan Image Local Variance EstimatoR (SILVER), for estimating the local noise level within each region of a CT image. The local noise level will be referred to as a pixel-wise noise map. Methods The SILVER architecture resembled a U-Net convolutional neural network with mean-square-error loss. To generate training data, 100 replicate scans were acquired of 3 anthropomorphic phantoms (chest, head, and pelvis) using a sequential scan mode; 120,000 phantom images were allocated into training, validation, and testing data sets. Pixel-wise noise maps were calculated for the phantom data by taking the per-pixel SD from the 100 replicate scans. For training, the convolutional neural network inputs consisted of phantom CT image patches, and the training targets consisted of the corresponding calculated pixel-wise noise maps. Following training, SILVER noise maps were evaluated using phantom and patient images. For evaluation on patient images, SILVER noise maps were compared with manual noise measurements at the heart, aorta, liver, spleen, and fat. Results When tested on phantom images, the SILVER noise map prediction closely matched the calculated noise map target (root mean square error <8 Hounsfield units). Within 10 patient examinations, SILVER noise map had an average percent error of 5% relative to manual region-of-interest measurements. Conclusion The SILVER framework enabled accurate pixel-wise noise level estimation directly from patient images. This method is widely accessible because it operates in the image domain and requires only phantom data for training.

Targeted delivery of magnetic nanoparticles (MNPs) to an area of a blood vessel with fluidic flow is hampered by the lack of a suitable real‐time imaging modality for MNPs, the control system complexity, and low targeting performance. Herein, an offline programming guidance (OLPG) scheme for aggregated MNPs is proposed based on a real‐time aggregation volume estimator. The proposed aggregation volume estimator based on a magnetic drug‐targeting simulator reflects volume changes of aggregated MNPs; hence, it can model a magnetic force acting on aggregated MNPs in real time while enhancing targeting performance. The proposed guidance system is evaluated using a simulation testbed and in vitro model of the rat brain, which yields comparable results at different fluid viscosities, flow velocities, target areas, and flow types. The OLPG with the aggregation volume estimator improves targeting performance by 116%–409% compared with the default mode, and by 111%–180% compared to the performance without the aggregation volume estimator. Furthermore, a guidance margin predicts enhanced targeting performance (root‐mean‐square error < 5%) irrespective of the flow environment. The proposed guidance strategy has the potential to overcome the problems caused by the lack of an imaging modality, control‐system complexity, and low targeting performance.

Management of patients with advanced sarcoma has been evolving in recent decades, from a one-fit-all perspective to a more refined, personalized, and multidisciplinary approach. In parallel, the evolution of local therapies (radiotherapy, surgical and interventional radiology techniques) has contributed to the improvement of survival of patients with advanced sarcoma. In this article, we review the evidence regarding local treatments in advanced sarcoma, as well as its integration with systemic therapies, to provide the reader a wider and deeper perspective on the management of patients with metastatic sarcoma.